Merge pull request #9 from Sunwood-ai-labs/translate-readme-11556071483

docs/README.en.md

@@ -31,7 +31,7 @@ license: mit
 </p>
 
 <h2 align="center">
-  ～ Llama Model Fine-tuning Experiment Environment ～
+  Llama Model Fine-tuning Experiment Environment
 </h2>
 
 <p align="center">
@@ -44,38 +44,40 @@ license: mit
 
 ## 🚀 Project Overview
 
-**Llama-finetune-sandbox** is an experimental environment for learning and verifying Llama model fine-tuning.  You can try various fine-tuning methods, customize models, and evaluate performance.  It caters to a wide range of users, from beginners to researchers.  Version 0.1.0 includes a repository name change, significantly updated README, and added a Llama model fine-tuning tutorial.
+**Llama-finetune-sandbox** provides an experimental environment for learning and verifying Llama model fine-tuning.  You can try various fine-tuning methods, customize models, and evaluate their performance.  It caters to a wide range of users, from beginners to researchers.  Version 0.1.0 includes a repository name change, a major README update, and the addition of a Llama model fine-tuning tutorial.
 
-## ✨ Key Features
+## ✨ Main Features
 
-1. **Various Fine-tuning Methods:**
+1. **Diverse Fine-tuning Methods**:
    - LoRA (Low-Rank Adaptation)
    - QLoRA (Quantized LoRA)
    - ⚠️~Full Fine-tuning~
    - ⚠️~Parameter-Efficient Fine-tuning (PEFT)~
 
-2. **Flexible Model Settings:**
+2. **Flexible Model Configuration**:
    - Customizable maximum sequence length
    - Various quantization options
    - Multiple attention mechanisms
 
-3. **Experimental Environment Setup:**
+3. **Well-Equipped Experiment Environment**:
    - Performance evaluation tools
    - Memory usage optimization
    - Visualization of experimental results
 
+## 📚 Examples
 
-## 📚 Implementation Examples
+This repository includes the following examples:
 
-This repository includes the following implementation examples:
+### High-Speed Fine-tuning using Unsloth
+ - High-speed fine-tuning implementation for Llama-3.2-1B/3B models
+   - → See [`Llama_3_2_1B+3B_Conversational_+_2x_faster_finetuning_JP.md`](sandbox/Llama_3_2_1B+3B_Conversational_+_2x_faster_finetuning_JP.md) for details.
+   - → [Use this to convert from Markdown to Notebook format](https://huggingface.co/spaces/MakiAi/JupytextWebUI)
+ - [📒Notebook here](https://colab.research.google.com/drive/1AjtWF2vOEwzIoCMmlQfSTYCVgy4Y78Wi?usp=sharing)
 
-1. **High-speed fine-tuning using Unsloth:**
-   - Implementation of high-speed fine-tuning for Llama-3.2-1B/3B models.
-     - → See [`Llama_3_2_1B+3B_Conversational_+_2x_faster_finetuning_JP.md`](sandbox/Llama_3_2_1B+3B_Conversational_+_2x_faster_finetuning_JP.md) for details.
-     - → [Use this to convert from Markdown to Notebook format](https://huggingface.co/spaces/MakiAi/JupytextWebUI)
-   - [📒Notebook here](https://colab.research.google.com/drive/1AjtWF2vOEwzIoCMmlQfSTYCVgy4Y78Wi?usp=sharing)
-
-2.  Other implementation examples will be added periodically.
+### Efficient Model Operation using Ollama and LiteLLM
+ - Setup and operation guide on Google Colab
+ - → See [`efficient-ollama-colab-setup-with-litellm-guide.md`](sandbox/efficient-ollama-colab-setup-with-litellm-guide.md) for details.
+ - [📒Notebook here](https://colab.research.google.com/drive/1buTPds1Go1NbZOLlpG94VG22GyK-F4GW?usp=sharing)
 
 ## 🛠️ Environment Setup
 
@@ -85,9 +87,9 @@ git clone https://github.com/Sunwood-ai-labs/Llama-finetune-sandbox.git
 cd Llama-finetune-sandbox
 ```
 
-## 📝 Adding Example Experiments
+## 📝 Adding Examples
 
-1. Add new implementations to the `examples/` directory.
+1. Add a new implementation to the `examples/` directory.
 2. Add necessary settings and utilities to `utils/`.
 3. Update documentation and tests.
 4. Create a pull request.